{
 "cells": [
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2 Physical GPUs, 2 Logical GPUs\n"
     ]
    }
   ],
   "source": [
    "import tensorflow as tf\n",
    "import graphgallery \n",
    "import matplotlib.pyplot as plt\n",
    "\n",
    "\n",
    "# Set if memory growth should be enabled for ALL `PhysicalDevice`.\n",
    "graphgallery.set_memory_growth()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'2.1.2'"
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tf.__version__"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "'0.4.0'"
      ]
     },
     "execution_count": 3,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "graphgallery.__version__"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Load the Datasets\n",
    "+ cora\n",
    "+ citeseer\n",
    "+ pubmed"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "from graphgallery.data import Planetoid\n",
    "\n",
    "# set `verbose=False` to avoid these printed tables\n",
    "data = Planetoid('cora', root=\"~/GraphData/datasets\", verbose=False)\n",
    "graph = data.graph\n",
    "idx_train, idx_val, idx_test = data.split()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'citeseer', 'cora', 'pubmed'}"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "data.supported_datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Training...\n",
      "100/100 [==============================] - 1s 12ms/step - loss: 1.3206 - acc: 0.8929 - val_loss: 1.6355 - val_acc: 0.7900 - time: 1.2465\n",
      "Testing...\n",
      "1/1 [==============================] - 0s 57ms/step - test_loss: 1.6229 - test_acc: 0.8140 - time: 0.0570\n",
      "Test loss 1.6229, Test accuracy 81.40%\n"
     ]
    }
   ],
   "source": [
    "from graphgallery.nn.models import SGC\n",
    "model = SGC(graph, order=2, attr_transform=\"normalize_attr\", device='GPU', seed=123)\n",
    "model.build()\n",
    "# train with validation\n",
    "his = model.train(idx_train, idx_val, verbose=1, epochs=100)\n",
    "# train without validation\n",
    "# his = model.train(idx_train, verbose=1, epochs=100)\n",
    "loss, accuracy = model.test(idx_test)\n",
    "print(f'Test loss {loss:.5}, Test accuracy {accuracy:.2%}')\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Show model summary"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "Model: \"sgc\"\n",
      "_________________________________________________________________\n",
      "Layer (type)                 Output Shape              Param #   \n",
      "=================================================================\n",
      "attr_matrix (InputLayer)     [(None, 1433)]            0         \n",
      "_________________________________________________________________\n",
      "dropout (Dropout)            (None, 1433)              0         \n",
      "_________________________________________________________________\n",
      "dense (Dense)                (None, 7)                 10038     \n",
      "=================================================================\n",
      "Total params: 10,038\n",
      "Trainable params: 10,038\n",
      "Non-trainable params: 0\n",
      "_________________________________________________________________\n"
     ]
    }
   ],
   "source": [
    "model.summary()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Visualization Training "
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 1080x360 with 2 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "import matplotlib.pyplot as plt\n",
    "with plt.style.context(['science', 'no-latex']):\n",
    "    fig, axes = plt.subplots(1, 2, figsize=(15, 5))\n",
    "    axes[0].plot(his.history['acc'], label='Train accuracy')\n",
    "    axes[0].plot(his.history['val_acc'], label='Val accuracy')\n",
    "    axes[0].legend()\n",
    "    axes[0].set_title('Accuracy')\n",
    "    axes[0].set_xlabel('Epochs')\n",
    "    axes[0].set_ylabel('Accuracy')\n",
    "\n",
    "\n",
    "    axes[1].plot(his.history['loss'], label='Training loss')\n",
    "    axes[1].plot(his.history['val_loss'], label='Validation loss')\n",
    "    axes[1].legend()\n",
    "    axes[1].set_title('Loss')\n",
    "    axes[1].set_xlabel('Epochs')\n",
    "    axes[1].set_ylabel('Loss')\n",
    "    \n",
    "    plt.autoscale(tight=True)\n",
    "    plt.show()    "
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.7.3"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
